Skin pharmacokinetics of miltefosine in the treatment of post-kala-azar dermal leishmaniasis in South Asia.

INTRODUCTION: Post-kala-azar dermal leishmaniasis (PKDL) arises as a dermal complication following a visceral leishmaniasis (VL) infection. Current treatment options for PKDL are unsatisfactory, and there is a knowledge gap regarding the distribution of antileishmanial compounds within human skin. The present study investigated the skin distribution of miltefosine in PKDL patients, with the aim to improve the understanding of the pharmacokinetics at the skin target site in PKDL. METHODS: Fifty-two PKDL patients underwent treatment with liposomal amphotericin B (20 mg/kg) plus miltefosine (allometric dosing) for 21 days. Plasma concentrations of miltefosine were measured on study days 8, 15, 22 and 30, while a punch skin biopsy was taken on day 22. A physiologically based pharmacokinetic (PBPK) model was developed to evaluate the distribution of miltefosine into the skin. RESULTS: Following the allometric weight-based dosing regimen, median miltefosine concentrations on day 22 were 43.73 µg/g (IQR: 21.94-60.65 µg/g) in skin and 33.29 µg/mL (IQR: 25.9-42.58 µg/mL) in plasma. The median individual concentration ratio of skin to plasma was 1.19 (IQR: 0.79-1.9). In 87% (45/52) of patients, skin exposure was above the suggested EC90 PK target of 10.6 mg/L associated with in vitro susceptibility. Simulations indicated that the residence time of miltefosine in the skin would be more than 2-fold longer than in plasma, estimated by a mean residence time of 604 versus 266 hours, respectively. CONCLUSION: This study provides the first accurate measurements of miltefosine penetration into the skin, demonstrating substantial exposure and prolonged retention of miltefosine within the skin. These findings support the use of miltefosine in cutaneous manifestations of leishmaniasis. In combination with parasitological and clinical data, these results are critical for the future optimization of combination therapies with miltefosine in the treatment of PKDL.

High accumulation of nivolumab in human breast milk: A case report.

Nivolumab is an immunotherapeutic monoclonal antibody (mAb) that is used for the treatment of several types of cancer. The evidence on its use during lactation is lacking. Here, we report on a 39-year-old woman with metastasized melanoma who was treated with 480 mg nivolumab every four weeks during lactation. Breast milk samples were collected over the course of 34 days, including two cycles of nivolumab. The highest measured concentration of nivolumab during the first cycle was 503 ng/mL at day 13. The cumulative relative infant dose (RID) over the first cycle (28 days) was 9.8 %. The highest overall measured nivolumab concentration was 519 ng/mL at day 33, five days after administration of the second nivolumab cycle. Nivolumab seems to accumulate in breast milk over two consecutive cycles, hence the RIDs of consecutive cycles are expected to be higher. To draw further conclusions regarding safety of breastfeeding during nivolumab therapy, more information about the oral bioavailability of nivolumab in newborns, the nivolumab steady-state concentrations in breast milk and its pharmacodynamic effects are needed.

Predicting [177Lu]Lu-HA-DOTATATE kidney and tumor accumulation based on [68Ga]Ga-HA-DOTATATE diagnostic imaging using semi-physiological population pharmacokinetic modeling.

BACKGROUND: Prediction of [177Lu]Lu-HA-DOTATATE kidney and tumor uptake based on diagnostic [68Ga]Ga-HA-DOTATATE imaging would be a crucial step for precision dosing of [177Lu]Lu-HA-DOTATATE. In this study, the population pharmacokinetic (PK) differences between [177Lu]Lu-HA-DOTATATE and [68Ga]Ga-HA-DOTATATE were assessed and subsequently [177Lu]Lu-HA-DOTATATE was predicted based on [68Ga]Ga-HA-DOTATATE imaging. METHODS: A semi-physiological nonlinear mixed-effects model was developed for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE, including six compartments (representing blood, spleen, kidney, tumor lesions, other somatostatin receptor expressing organs and a lumped rest compartment). Model parameters were fixed based on a previously developed physiologically based pharmacokinetic model for [68Ga]Ga-HA-DOTATATE. For [177Lu]Lu-HA-DOTATATE, PK parameters were based on literature values or estimated based on scan data (four time points post-injection) from nine patients. Finally, individual [177Lu]Lu-HA-DOTATATE uptake into tumors and kidneys was predicted based on individual [68Ga]Ga-HA-DOTATATE scan data using Bayesian estimates. Predictions were evaluated compared to observed data using a relative prediction error (RPE) for both area under the curve (AUC) and absorbed dose. Lastly, to assess the predictive value of diagnostic imaging to predict therapeutic exposure, individual prediction RPEs (using Bayesian estimation) were compared to those from population predictions (using the population model). RESULTS: Population uptake rate parameters for spleen, kidney and tumors differed by a 0.29-fold (15% relative standard error (RSE)), 0.49-fold (15% RSE) and 1.43-fold (14% RSE), respectively, for [177Lu]Lu-HA-DOTATATE compared to [68Ga]Ga-HA-DOTATATE. Model predictions adequately described observed data in kidney and tumors for both peptides (based on visual inspection of goodness-of-fit plots). Individual predictions of tumor uptake were better (RPE AUC -40 to 28%) compared to kidney predictions (RPE AUC -53 to 41%). Absorbed dose predictions were less predictive for both tumor and kidneys (RPE tumor and kidney -51 to 44% and -58 to 82%, respectively). For most patients, [177Lu]Lu-HA-DOTATATE tumor accumulation predictions based on individual PK parameters estimated from diagnostic imaging outperformed predictions based on population parameters. CONCLUSION: Our semi-physiological PK model indicated clear differences in PK parameters for [68Ga]Ga-HA-DOTATATE and [177Lu]Lu-HA-DOTATATE. Diagnostic images provided additional information to individually predict [177Lu]Lu-HA-DOTATATE tumor uptake compared to using a population approach. In addition, individual predictions indicated that many aspects, apart from PK differences, play a part in predicting [177Lu]Lu-HA-DOTATATE distribution.

Optimizing carboplatin dosing by an improved prediction of carboplatin clearance using a CT-enhanced estimate of renal function.

AIMS: Carboplatin is generally dosed based on a modified Calvert formula, in which the Cockcroft-Gault-based creatinine clearance (CRCL) is used as proxy for the glomerular filtration rate (GFR). The Cockcroft-Gault formula (CG) overpredicts CRCL in patients with an aberrant body composition. The CT-enhanced estimate of RenAl FuncTion (CRAFT) was developed to compensate for this overprediction. We aimed to evaluate whether carboplatin clearance is better predicted by CRCL based on the CRAFT compared to the CG. METHODS: Data of four previously conducted trials was used. The CRAFT was divided by serum creatinine to derive CRCL. The difference between CRAFT- and CG-based CRCL was assessed by population pharmacokinetic modelling. Furthermore, the difference in calculated carboplatin dose was assessed in a heterogeneous dataset. RESULTS: In total, 108 patients were included in the analysis. Addition of the CRAFT- and CG-based CRCL as covariate on carboplatin clearance led, respectively, to an improved model fit with a 26-point drop in objective function value and a worsened model fit with an increase of 8 points. In 19 subjects with serum creatinine <50 µmol/L, the calculated carboplatin dose was 233 mg higher using the CG. CONCLUSIONS: Carboplatin clearance is better predicted by CRAFT vs. CG-based CRCL. In subjects with low serum creatinine, the calculated carboplatin dose using CG exceeds the dose using CRAFT, which might explain the need for dose capping when using the CG. Therefore, the CRAFT might be an alternative for dose capping while still dosing accurately.

Development of a Therapeutic Drug Monitoring Strategy for the Optimization of Vincristine Treatment in Pediatric Oncology Populations in Africa.

BACKGROUND: Recent studies have reported ethnic differences in vincristine exposure and outcomes such as toxicity. This resulted in the hypothesis of subtherapeutic dosing in African children. To optimize individual treatment, a strategy to identify subtherapeutic exposure using therapeutic drug monitoring is essential. The aim of the current study was to develop a strategy for therapeutic drug monitoring of vincristine in African children to meet the following criteria: (1) identify patients with low vincristine exposure with sufficient sensitivity (>70%), (2) determine vincristine exposure with a limited sampling strategy design of 3 samples, and (3) allow all samples to be collected within 4 hours after administration. METHODS: An in silico simulation study was performed using a previously described population pharmacokinetic model and real-life demographic dataset of Kenyan and Malawian pediatric oncology patients. Two different therapeutic drug monitoring strategies were evaluated: (1) Bayesian approach and (2) pharmacometric nomogram. The sampling design was optimized using the constraints described above. Sensitivity analysis was performed to investigate the influence of missing samples, erroneous sampling times, and different boundaries on the nomogram weight bands. RESULTS: With the Bayesian approach, 43.3% of the estimated individual exposure values had a prediction error of ≥20% owing to extremely high shrinkage. The Bayesian approach did not improve with alternative sampling designs within sampling constraints. However, the pharmacometric nomogram could identify patients with low vincristine exposure with a sensitivity, specificity, and accuracy of 75.1%, 76.4%, and 75.9%, respectively. The pharmacometric nomogram performed similarly for different weight bands. CONCLUSIONS: The pharmacometric nomogram was able to identify patients with low vincristine exposure with high sensitivity, with 3 blood samples collected at 1, 1.5, and 4 hours after administration. Missing samples should be avoided, and the 3 scheduled samples should be collected within 15, 5, and 15 minutes of 1, 1.5, and 4 hours after administration, respectively.

A physiologically based pharmacokinetic model for [68Ga]Ga-(HA-)DOTATATE to predict whole-body distribution and tumor sink effects in GEP-NET patients.

BACKGROUND: Little is known about parameters that have a relevant impact on (dis)similarities in biodistribution between various 68Ga-labeled somatostatin analogues. Additionally, the effect of tumor burden on organ uptake remains unclear. Therefore, the aim of this study was to describe and compare organ and tumor distribution of [68Ga]Ga-DOTATATE and [68Ga]Ga-HA-DOTATATE using a physiologically based pharmacokinetic (PBPK) model and to identify factors that might cause biodistribution and tumor uptake differences between both peptides. In addition, the effect of tumor burden on peptide biodistribution in gastroenteropancreatic (GEP) neuroendocrine tumor (NET) patients was assessed. METHODS: A PBPK model was developed for [68Ga]Ga-(HA-)DOTATATE in GEP-NET patients. Three tumor compartments were added, representing primary tumor, liver metastases and other metastases. Furthermore, reactions describing receptor binding, internalization and recycling, renal clearance and intracellular degradation were added to the model. Scan data from GEP-NET patients were used for evaluation of model predictions. Simulations with increasing tumor volumes were performed to assess the tumor sink effect. RESULTS: Data of 39 and 59 patients receiving [68Ga]Ga-DOTATATE and [68Ga]Ga-HA-DOTATATE, respectively, were included. Evaluations showed that the model adequately described image-based patient data and that different receptor affinities caused organ uptake dissimilarities between both peptides. Sensitivity analysis indicated that tumor blood flow and blood volume impacted tumor distribution most. Tumor sink predictions showed a decrease in spleen uptake with increasing tumor volume, which seemed clinically relevant for patients with total tumor volumes higher than ~ 550 mL. CONCLUSION: The developed PBPK model adequately predicted tumor and organ uptake for this GEP-NET population. Relevant organ uptake differences between [68Ga]Ga-DOTATATE and [68Ga]Ga-HA-DOTATATE were caused by different affinity profiles, while tumor uptake was mainly affected by tumor blood flow and blood volume. Furthermore, tumor sink predictions showed that for the majority of patients a tumor sink effect is not expected to be clinically relevant.

Population pharmacokinetic dosimetry model using imaging data to assess variability in pharmacokinetics of 177 Lu-PSMA-617 in prostate cancer patients.

Studies to evaluate and optimize [177 Lu]Lu-PSMA treatment focus primarily on individual patient data. A population pharmacokinetic (PK) dosimetry model was developed to explore the potential of using imaging data as input for population PK models and to characterize variability in organ and tumor uptake of [177 Lu]Lu-PSMA-617 in patients with low volume metastatic prostate cancer. Simulations were performed to identify the effect of dose adjustments on absorbed doses in salivary glands and tumors. A six-compartment population PK model was developed, consisting of blood, salivary gland, kidneys, liver, tumor, and a lumped compartment representing other tissue (compartment 1-6, respectively), based on data from 10 patients who received [177 Lu]Lu-PSMA-617 (2 cycles, ~ 3 and ~ 6 GBq). Data consisted of radioactivity levels (decay corrected) in blood and tissues (9 blood samples and 5 single photon emission computed tomography/computed tomography scans). Observations in all compartments were adequately captured by individual model predictions. Uptake into salivary glands was saturable with an estimated maximum binding capacity (Bmax ) of 40.4 MBq (relative standard error 12.3%) with interindividual variability (IIV) of 59.3% (percent coefficient of variation [CV%]). IIV on other PK parameters was relatively minor. Tumor volume was included as a structural effect on the tumor uptake rate constant (k15 ), where a two-fold increase in tumor volume resulted in a 1.63-fold increase in k15 . In addition, interoccasion variability on k15 improved the model fit (43.5% [CV%]). Simulations showed a reduced absorbed dose per unit administered activity for salivary glands after increasing radioactivity dosing from 3 to 6 GBq (0.685 Gy/GBq vs. 0.421 Gy/GBq, respectively). All in all, population PK modeling could help to improve future radioligand therapy research.

Semi-mechanistic Modeling of Hypoxanthine, Xanthine, and Uric Acid Metabolism in Asphyxiated Neonates.

BACKGROUND AND OBJECTIVE: Previously, we developed a pharmacokinetic-pharmacodynamic model of allopurinol, oxypurinol, and biomarkers, hypoxanthine, xanthine, and uric acid, in neonates with hypoxic-ischemic encephalopathy, in which high initial biomarker levels were observed suggesting an impact of hypoxia. However, the full pharmacodynamics could not be elucidated in our previous study. The current study included additional data from the ALBINO study (NCT03162653) placebo group, aiming to characterize the dynamics of hypoxanthine, xanthine, and uric acid in neonates with hypoxic-ischemic encephalopathy. METHODS: Neonates from the ALBINO study who received allopurinol or placebo mannitol were included. An extended population pharmacokinetic-pharmacodynamic model was developed based on the mechanism of purine metabolism, where synthesis, salvage, and degradation via xanthine oxidoreductase pathways were described. The initial level of the biomarkers was a combination of endogenous turnover and high disease-related amounts. Model development was accomplished by nonlinear mixed-effects modeling (NONMEM®, version 7.5). RESULTS: In total, 20 neonates treated with allopurinol and 17 neonates treated with mannitol were included in this analysis. Endogenous synthesis of the biomarkers reduced with 0.43% per hour because of precursor exhaustion. Hypoxanthine was readily salvaged or degraded to xanthine with rate constants of 0.5 1/h (95% confidence interval 0.33-0.77) and 0.2 1/h (95% confidence interval 0.09-0.31), respectively. A greater salvage was found in the allopurinol treatment group consistent with its mechanism of action. High hypoxia-induced initial levels of biomarkers were quantified, and were 1.2-fold to 2.9-fold higher in neonates with moderate-to-severe hypoxic-ischemic encephalopathy compared with those with mild hypoxic-ischemic encephalopathy. Half-maximal xanthine oxidoreductase inhibition was achieved with a combined allopurinol and oxypurinol concentration of 0.68 mg/L (95% confidence interval 0.48-0.92), suggesting full xanthine oxidoreductase inhibition during the period studied. CONCLUSIONS: This extended pharmacokinetic-pharmacodynamic model provided an adequate description of the complex hypoxanthine, xanthine, and uric acid metabolism in neonates with hypoxic-ischemic encephalopathy, suggesting a positive allopurinol effect on these biomarkers. The impact of hypoxia on their dynamics was characterized, underlining higher hypoxia-related initial exposure with a more severe hypoxic-ischemic encephalopathy status.

Development of a population pharmacokinetic/pharmacodynamic model for various oral paclitaxel formulations co-administered with ritonavir and thrombospondin-1 based on data from early phase clinical studies.

PURPOSE: Orally administered paclitaxel offers increased patient convenience while providing a method to prolong exposure without long continuous, or repeated, intravenous infusions. The oral bioavailability of paclitaxel is improved through co-administration with ritonavir and application of a suitable pharmaceutical formulation, which addresses the dissolution-limited absorption of paclitaxel. We aimed to characterize the pharmacokinetics of different paclitaxel formulations, co-administered with ritonavir, and to investigate a pharmacodynamic relationship between low-dose metronomic (LDM) treatment with oral paclitaxel and the anti-angiogenic marker thrombospondin-1 (TSP-1). METHODS: Fifty-eight patients treated with different oral paclitaxel formulations were included for pharmacokinetic analysis. Pharmacodynamic data was available for 36 patients. All population pharmacokinetic/pharmacodynamic modelling was performed using non-linear mixed-effects modelling. RESULTS: A pharmacokinetic model consisting of gut, liver, central, and peripheral compartments was developed for paclitaxel. The gastrointestinal absorption rate was modelled with a Weibull function. Relative gut bioavailabilities of the tablet and capsule formulations, as fractions of the gut bioavailability of the drinking solution, were estimated to be 0.97 (95%CI: 0.67-1.33) and 0.46 (95%CI: 0.34-0.61), respectively. The pharmacokinetic/pharmacodynamic relationship between paclitaxel and TSP-1 was modelled using a turnover model with paclitaxel plasma concentrations driving an increase in TSP-1 formation rate following an Emax relationship with an EC50 of 284 ng/mL (95%CI: 122-724). CONCLUSION: The developed pharmacokinetic model adequately described the paclitaxel plasma concentrations for the different oral formulations co-administered with ritonavir. This model, and the established pharmacokinetic/pharmacodynamic relationship with TSP-1, may facilitate future development of oral paclitaxel.

Longitudinal nonlinear mixed effects modeling of EGFR mutations in ctDNA as predictor of disease progression in treatment of EGFR-mutant non-small cell lung cancer.

Correlations between increasing concentrations of circulating tumor DNA (ctDNA) in plasma and disease progression have been shown. A nonlinear mixed effects model to describe the dynamics of epidermal growth factor receptor (EGFR) ctDNA data from patients with non-small cell lung cancer (NSCLC) combined with a parametric survival model were developed to evaluate the ability of these modeling techniques to describe ctDNA data. Repeated ctDNA measurements on L858R, exon19del, and T790M mutants were available from 54 patients with EGFR mutated NSCLC treated with erlotinib or gefitinib. Different dynamic models were tested to describe the longitudinal ctDNA concentrations of the driver and resistance mutations. Subsequently, a parametric time-to-event model for progression-free survival (PFS) was developed. Predicted L858R, exon19del, and T790M concentrations were used to evaluate their value as predictor for disease progression. The ctDNA dynamics were best described by a model consisting of a zero-order increase and first-order elimination (19.7/day, 95% confidence interval [CI] 14.9-23.6/day) of ctDNA concentrations. In addition, time-dependent development of resistance (5.0 × 10-4 , 95% CI 2.0 × 10-4 -7.0 × 10-4 /day) was included in the final model. Relative change in L858R and exon19del concentrations from baseline was identified as most significant predictor of disease progression (p = 0.001). The dynamic model for L858R, exon19del, and T790M concentrations in ctDNA and time-to-event model adequately described the observed concentrations and PFS data in our clinical cohort. In addition, it was shown that nonlinear mixed effects modeling is a valuable method for the analysis of longitudinal and heterogeneous biomarker datasets obtained from clinical practice.

Everolimus Concentration in Saliva to Predict Stomatitis: A Feasibility Study in Patients with Cancer.

BACKGROUND: Most patients with cancer treated with everolimus experience stomatitis, which seriously affects the quality of life. The salivary concentrations of everolimus may predict the incidence and severity of stomatitis. The authors aimed to examine whether it was feasible to quantify the everolimus concentration in saliva and subsequently use it to predict stomatitis. METHODS: Saliva and whole blood samples were taken from patients with cancer, who were treated with everolimus in the dosage of either 10 mg once a day or 5 mg twice a day. Everolimus concentrations in saliva samples were measured by liquid chromatography-tandem mass spectrometry. A published population pharmacokinetic model was extended with the everolimus concentration in saliva to assess any association between everolimus in the blood and saliva. Subsequently, the association between the occurrence of stomatitis and the everolimus concentration in saliva was studied. RESULTS: Eleven patients were included in this study; saliva samples were available from 10 patients, including 3 patients with low-grade stomatitis. Everolimus concentrations were more than 100-fold lower in saliva than in whole blood (accumulation ratio 0.00801 and relative standard error 32.5%). Interindividual variability (67.7%) and residual unexplained variability (84.0%) were high. The salivary concentration of everolimus tended to be higher in patients with stomatitis, 1 hour postdose ( P = 0.14). CONCLUSIONS: Quantification of the everolimus concentration in saliva was feasible and revealed a nonsignificant correlation between everolimus concentration in the saliva and the occurrence of stomatitis. If future research proves this relationship to be significant, the everolimus concentration in the saliva may be used as an early predictor of stomatitis without invasive sampling. Thereby, in patients with high salivary everolimus concentrations, precautions can be taken to decrease the incidence and severity of stomatitis.

Pharmacokinetic/Pharmacodynamic Modelling of Allopurinol, its Active Metabolite Oxypurinol, and Biomarkers Hypoxanthine, Xanthine and Uric Acid in Hypoxic-Ischemic Encephalopathy Neonates.

BACKGROUND: Allopurinol, an xanthine oxidase (XO) inhibitor, is a promising intervention that may provide neuroprotection for neonates with hypoxic-ischemic encephalopathy (HIE). Currently, a double-blind, placebo-controlled study (ALBINO, NCT03162653) is investigating the neuroprotective effect of allopurinol in HIE neonates. OBJECTIVE: The aim of the current study was to establish the pharmacokinetics (PK) of allopurinol and oxypurinol, and the pharmacodynamics (PD) of both compounds on hypoxanthine, xanthine, and uric acid in HIE neonates. The dosage used and the effect of allopurinol in this population, either or not undergoing therapeutic hypothermia (TH), were evaluated. METHODS: Forty-six neonates from the ALBINO study and two historical clinical studies were included. All doses were administered on the first day of life. In the ALBINO study (n = 20), neonates received a first dose of allopurinol 20 mg/kg, and, in the case of TH (n = 13), a second dose of allopurinol 10 mg/kg. In the historical cohorts (n = 26), neonates (all without TH) received two doses of allopurinol 20 mg/kg in total. Allopurinol and oxypurinol population PK, and their effects on inhibiting conversions of hypoxanthine and xanthine to uric acid, were assessed using nonlinear mixed-effects modelling. RESULTS: Allopurinol and oxypurinol PK were described by two sequential one-compartment models with an autoinhibition effect on allopurinol metabolism by oxypurinol. For allopurinol, clearance (CL) was 0.83 L/h (95% confidence interval [CI] 0.62-1.09) and volume of distribution (Vd) was 2.43 L (95% CI 2.25-2.63). For metabolite oxypurinol, CL and Vd relative to a formation fraction (fm) were 0.26 L/h (95% CI 0.23-0.3) and 11 L (95% CI 9.9-12.2), respectively. No difference in allopurinol and oxypurinol CL was found between TH and non-TH patients. The effect of allopurinol and oxypurinol on XO inhibition was described by a turnover model of hypoxanthine with sequential metabolites xanthine and uric acid. The combined allopurinol and oxypurinol concentration at the half-maximal XO inhibition was 0.36 mg/L (95% CI 0.31-0.42). CONCLUSION: The PK and PD of allopurinol, oxypurinol, hypoxanthine, xanthine, and uric acid in neonates with HIE were described. The dosing regimen applied in the ALBINO trial leads to the targeted XO inhibition in neonates treated with or without TH.

Population Pharmacokinetic Modelling to Support the Evaluation of Preclinical Pharmacokinetic Experiments with Lorlatinib.

The effect of transporters and enzymes on drug pharmacokinetics is increasingly evaluated using genetically modified animals that have these proteins either knocked-out or their human orthologues transgenically expressed. Analysis of pharmacokinetic data obtained in such experiments is typically performed using non-compartmental analysis (NCA), which has limitations such as not being able to identify the PK parameter that is affected by the genetic modification of the enzymes or transporters and the requirement of intense and homogeneous sampling of all subjects. Here we used a compartmental population pharmacokinetic modeling approach using PK data from a series of genetically modified mouse experiments with lorlatinib to extend the results and conclusions from previously reported NCA analyses. A compartmental population pharmacokinetic model was built and physiologically plausible covariates were evaluated for the different mouse strains. With the model, similar effects of the strains on the area under the concentration-time curve (AUC) from 0 to 8 hours were found as for the NCA. Additionally, the differences in AUC between the strains were explained by specific effects on clearance and bioavailability for the strain with human expressing CYP3A4. Finally, effects of multidrug efflux transporters ATP-binding cassette (ABC) sub-family B member 1 (ABCB1) and G member 2 (ABCG2) on brain efflux were quantified. Use of compartmental population PK modeling yielded additional insight into the role of drug-metabolizing enzymes and drug transporters in mouse experiments compared to the NCA. Furthermore, these models allowed analysis of heterogeneous pooled datasets and the sparse organ concentration data in contrast to classical NCA analyses.

Toxicity of pemetrexed during renal impairment explained-Implications for safe treatment.

Pemetrexed is an important component of first line treatment in patients with non-squamous non-small cell lung cancer. However, a limitation is the contraindication in patients with renal impairment due to hematological toxicity. Currently, it is unknown how to safely dose pemetrexed in these patients. The aim of our study was to elucidate the relationship between pemetrexed exposure and toxicity to support the development of a safe dosing regimen in patients with renal impairment. A population pharmacokinetic/pharmacodynamic analysis was performed based on phase II study results in three patients with renal dysfunction, supplemented with data from 106 patients in early clinical studies. Findings were externally validated with data of different pemetrexed dosing regimens. Alternative dosing regimens were evaluated using the developed model. We found that pemetrexed toxicity was driven by the time above a toxicity threshold concentration. The threshold for vitamin-supplemented patients was 0.110 mg/mL (95% CI: 0.092-0.146 mg/mL). It was observed that in patients with renal impairment (estimated glomerular filtration rate [eGFR]: <45 mL/min) the approved dose of 500 mg/m2 would yield a high probability of severe neutropenia in the range of 51.0% to 92.6%. A pemetrexed dose of 20 mg for patients (eGFR: 20 mL/min) is shown to be neutropenic-equivalent to the approved dose in patients with adequate renal function (eGFR: 90 mL/min), but would result in an approximately 13-fold lower area under the concentration-time curve. The pemetrexed exposure-toxicity relationship is explained by a toxicity threshold and substantially different from previously thought. Without prophylaxis for toxicity, it is unlikely that a therapeutic dose can be safely administered to patients with renal impairment.

Investigating the influence of relevant pharmacogenetic variants on the pharmacokinetics and pharmacodynamics of orally administered docetaxel combined with ritonavir.

The anticancer drug docetaxel exhibits large interpatient pharmacokinetic and pharmacodynamic variability. In this study, we aimed to assess the functional significance of 14 polymorphisms in the CYP3A, CYP1B1, ABCB1, ABCC2, and SLCO1B3 genes for the pharmacokinetics and pharmacodynamics of oral docetaxel, co-administered with ritonavir. None of the tested CYP3A, ABCB1, ABCC2, and SLCO1B3 genotypes and diplotypes showed a significant relation with an altered bioavailability or clearance of either docetaxel or ritonavir. Similarly, no clear effect of CYP1B1 genotype on clinical outcomes was observed in a subgroup of non-small cell lung cancer (NSCLC) patients. Our post hoc power analysis indicated that our pharmacogenetic-pharmacokinetic analysis was only powered for relatively high effect sizes, which were to be expected given the high interpatient variability. This makes it unlikely that future studies will explain the high observed interpatient variability in oral docetaxel pharmacokinetics as a result of any of these separate polymorphisms and diplotypes.

Population Pharmacokinetics of Docetaxel, Paclitaxel, Doxorubicin and Epirubicin in Pregnant Women with Cancer: A Study from the International Network of Cancer, Infertility and Pregnancy (INCIP).

BACKGROUND: Based on reassuring short-term foetal and maternal safety data, there is an increasing trend to administer chemotherapy during the second and third trimesters of pregnancy. The pharmacokinetics (PK) of drugs might change as a result of several physiological changes that occur during pregnancy, potentially affecting the efficacy and safety of chemotherapy. OBJECTIVE: With this analysis, we aimed to quantitatively describe the changes in the PK of docetaxel, paclitaxel, doxorubicin and epirubicin in pregnant women compared with non-pregnant women. METHODS: PK data from 9, 20, 22 and 16 pregnant cancer patients from the International Network of Cancer, Infertility and Pregnancy (INCIP) were available for docetaxel, paclitaxel, doxorubicin and epirubicin, respectively. These samples were combined with available PK data from non-pregnant patients. Empirical non-linear mixed-effects models were developed, evaluating fixed pregnancy effects and gestational age as covariates. RESULTS: Overall, 82, 189, 271, and 227 plasma samples were collected from pregnant patients treated with docetaxel, paclitaxel, doxorubicin and epirubicin, respectively. The plasma PK data were adequately described by the respective models for all cytotoxic drugs. Typical increases in central and peripheral volumes of distribution of pregnant women were identified for docetaxel, paclitaxel, doxorubicin and epirubicin. Additionally, docetaxel, doxorubicin and paclitaxel clearance were increased in pregnant patients, resulting in lower exposure in pregnant women compared with non-pregnant patients. CONCLUSION: Given the interpatient variability, the identified pregnancy-induced changes in PK do not directly warrant dose adjustments for the studied drugs. Nevertheless, these results underscore the need to investigate the efficacy of chemotherapy, when administered during pregnancy.

Population Pharmacokinetics of Intracellular 5-Fluorouridine 5'-Triphosphate and its Relationship with Hand-and-Foot Syndrome in Patients Treated with Capecitabine.

Capecitabine is an oral pro-drug of 5-fluorouracil. Patients with solid tumours who are treated with capecitabine may develop hand-and-foot syndrome (HFS) as side effect. This might be a result of accumulation of intracellular metabolites. We characterised the pharmacokinetics (PK) of 5-fluorouridine 5'-triphosphate (FUTP) in peripheral blood mononuclear cells (PBMCs) and assessed the relationship between exposure to capecitabine or its metabolites and the development of HFS. Plasma and intracellular capecitabine PK data and ordered categorical HFS data was available. A previously developed model describing the PK of capecitabine and metabolites was extended to describe the intracellular FUTP concentrations. Subsequently, a continuous-time Markov model was developed to describe the development of HFS during treatment with capecitabine. The influences of capecitabine and metabolite concentrations on the development of HFS were evaluated. The PK of intracellular FUTP was described by an one-compartment model with first-order elimination (ke,FUTP was 0.028 h-1 (95% confidence interval 0.022-0.039)) where the FUTP influx rate was proportional to the 5-FU plasma concentrations. The predicted individual intracellular FUTP concentration was identified as a significant predictor for the development and severity of HFS. Simulations demonstrated a clear exposure-response relationship. The intracellular FUTP concentrations were successfully described and a significant relationship between these intracellular concentrations and the development and severity of HFS was identified. This model can be used to simulate future dosing regimens and thereby optimise treatment with capecitabine.

Population pharmacokinetic analysis of nanoparticle-bound and free camptothecin after administration of NLG207 in adults with advanced solid tumors.

PURPOSE: NLG207 (formerly CRLX101) is a nanoparticle-drug conjugate (NDC) of the potent topoisomerase I inhibitor, camptothecin (CPT). The present study sought to characterize the complex pharmacokinetics (PK) of NLG207 and better describe CPT release from nanoparticles using a population PK (popPK) model. METHODS: From 27 patients enrolled on two phase II clinical trials (NCT02769962 and NCT03531827), dense sampling was performed up to 48 h post-administration of NLG207 during cycle one and six of treatment; samples were also collected at ~ 360 h post-dose. Conjugated and free CPT concentrations were quantified from each sample, resulting in 477 observations to build a popPK model using non-linear mixed-effects modeling. RESULTS: The PK of NLG207 was characterized by combining two linear two-compartment models with first-order kinetics each to describe nanoparticle-bound (conjugated) and free CPT. Allometric scaling based on body weight provided the best body-size descriptor for all PK parameters. The typical volumes of distribution of the conjugated CPT central and free CPT central compartments were 3.16 L (BSV CV%; 18.1%) and 21.1 L (CV%; 79.8%), respectively. CPT release from the nanoparticle formulation was characterized via an initial rapid clearance of 5.71 L/h (CV%; 62.6%), which decreased via first-order decay (estimated half-life of 0.307 h) to the steady-state value of 0.0988 L/h (CV%; 33.5%) by ~ 4 h after end of infusion. Renal clearance of free CPT was 0.874 L/h (CV%; 42.2%). CONCLUSION: The popPK model confirmed nanoparticle behavior of conjugated CPT and mechanistically characterized CPT release from NLG207. The current analysis provides a strong foundation for future study as a potential predictive tool in ongoing NLG207 clinical trials.

Evaluation of Extrapolation Methods to Predict Trough Concentrations to Guide Therapeutic Drug Monitoring of Oral Anticancer Drugs.

BACKGROUND: For oral anticancer drugs, trough concentration (Cmin) is usually used as a target in therapeutic drug monitoring (TDM). Recording of Cmin is highly challenging in outpatients, in whom there is typically a variability in sample collection time after dosing. Various methods are used to estimate Cmin from the collected samples. This simulation study aimed to evaluate the performance of 3 different methods in estimating the Cmin of 4 oral anticancer drugs for which TDM is regularly performed. METHODS: Plasma concentrations of abiraterone, dabrafenib, imatinib, and pazopanib at a random time (Ct,sim) and at the end of the dosing interval (Cmin,sim) were simulated from population pharmacokinetic models including 1000 patients, and the values were converted into simulated observed concentrations (Ct,sim,obs and Cmin,sim,obs) by adding a residual error. From Ct, sim,obs, Cmin was predicted (Cmin,pred) by the Bayesian estimation (method 1), taking the ratio of the Ct,sim,obs and typical population concentration and multiplying this ratio with the typical population value of Cmin,sim (method 2), and log-linear extrapolation (method 3). Target attainment was assessed by comparing Cmin,pred with the proposed pharmacokinetic targets related to efficacy and calculating the positive predictive and negative predictive values. RESULTS: The mean relative prediction error and root mean squared relative prediction error results showed that method 3 was out-performed by method 1 and 2. Target attainment was adequately predicted by all 3 methods (the respective positive predictive value of method 1, 2, and 3 was 92.1%, 92.5%, and 93.1% for abiraterone; 87.3%, 86.9%, and 99.1% for dabrafenib; 79.3%, 79.3%, and 75.9% for imatinib; and 72.5%, 73.5%, and 67.6% for pazopanib), indicating that dose adjustments were correctly predicted. CONCLUSIONS: Both method 1 and 2 provided accurate and precise individual Cmin,pred values. However, method 2 was easier to implement than method 1 to guide individual dose adjustments in TDM programs.

Quantification of the pharmacokinetic-toxicodynamic relationship of oral docetaxel co-administered with ritonavir.

Introduction Oral formulations of docetaxel have successfully been developed as an alternative for intravenous administration. Co-administration with the enzyme inhibitor ritonavir boosts the docetaxel plasma exposure. In dose-escalation trials, the maximum tolerated doses for two different dosing regimens were established and dose-limiting toxicities (DLTs) were recorded. The aim of current analysis was to develop a pharmacokinetic (PK)-toxicodynamic (TOX) model to quantify the relationship between docetaxel plasma exposure and DLTs. Methods A total of 85 patients was included in the current analysis, 18 patients showed a DLT in the four-week observation period. A PK-TOX model was developed and simulations based on the PK-TOX model were performed. Results The final PK-TOX model was characterized by an effect compartment representing the toxic effect of docetaxel, which was linked to the probability of developing a DLT. Simulations of once-weekly, once-daily 60 mg and once-weekly, twice-daily 30 mg followed by 20 mg of oral docetaxel suggested that 14% and 34% of patients, respectively, would have a probability >25% to develop a DLT in a four-week period. Conclusions A PK-TOX model was successfully developed. This model can be used to evaluate the probability of developing a DLT following treatment with oral docetaxel and ritonavir in different dosing regimens.